NDLI: Efficient Image Dehazing with Boundary Constraint and Contextual Regularization

Content Provider	IEEE Xplore Digital Library
Author	Gaofeng Meng Ying Wang Jiangyong Duan Shiming Xiang Chunhong Pan
Copyright Year	2013
Description	Author affiliation: Nat. Lab. of Pattern Recognition, Inst. of Autom., Beijing, China (Gaofeng Meng; Ying Wang; Jiangyong Duan; Shiming Xiang; Chunhong Pan)
Abstract	Images captured in foggy weather conditions often suffer from bad visibility. In this paper, we propose an efficient regularization method to remove hazes from a single input image. Our method benefits much from an exploration on the inherent boundary constraint on the transmission function. This constraint, combined with a weighted $L_{1}-norm$ based contextual regularization, is modeled into an optimization problem to estimate the unknown scene transmission. A quite efficient algorithm based on variable splitting is also presented to solve the problem. The proposed method requires only a few general assumptions and can restore a high-quality haze-free image with faithful colors and fine image details. Experimental results on a variety of haze images demonstrate the effectiveness and efficiency of the proposed method.
Sponsorship	IEEE Comput. Soc.
Starting Page	617
Ending Page	624
File Size	1446438
Page Count	8
File Format	PDF
ISBN	9781479928408
ISSN	15505499
DOI	10.1109/ICCV.2013.82
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-01
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image color analysis Atmospheric modeling Image edge detection Estimation Optimization Extrapolation Meteorology visibility enhancement image processing single image dehazing
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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